def test_nan_before_size(self):
bar = self.app_context.inst_data_mgr.get_series("bar")
bar.start(self.app_context)
stddev = StdDev(bar, input_key='close', length=3)
stddev.start(self.app_context)
t1 = datetime.datetime.now()
nextTime = lambda t: t + datetime.timedelta(0, 3)
x = np.random.normal(0, 2.0, 3)
ts = np.cumsum(x) + 100
i = 0
bar.add({"timestamp": t1, "close": ts[i], "open": 0})
self.assertEquals([{
"name": "'%s'" % stddev.name,
"timestamp": t1,
'value': np.nan
}], stddev.get_data())
t2 = nextTime(t1)
i = i + 1
bar.add({"timestamp": t2, "close": ts[i], "open": 1.4})
self.assertEquals([{
"name": "'%s'" % stddev.name,
"timestamp": t1,
'value': np.nan
}, {
"name": "'%s'" % stddev.name,
"timestamp": t2,
'value': np.nan
}], stddev.get_data())
t3 = nextTime(t2)
i = i + 1
bar.add({"timestamp": t3, "close": ts[i], "open": 1.8})
self.assertEquals([{
"name": "'%s'" % stddev.name,
"timestamp": t1,
'value': np.nan
}, {
"name": "'%s'" % stddev.name,
"timestamp": t2,
'value': np.nan
}, {
"name": "'%s'" % stddev.name,
"timestamp": t3,
'value': np.std(ts)
}], stddev.get_data())
def test_nan_before_size(self):
bar = self.app_context.inst_data_mgr.get_series("bar")
bar.start(self.app_context)
stddev = StdDev(inputs=bar, input_keys='close', length=3)
stddev.start(self.app_context)
t1 = 1
nextTime = lambda t: t + 3
x = np.random.normal(0, 2.0, 3)
ts = np.cumsum(x) + 100
i = 0
bar.add(timestamp=t1, data={"close": ts[i], "open": 0})
self.assertEquals([{'value': np.nan}], stddev.get_data())
t2 = nextTime(t1)
i = i + 1
bar.add(timestamp=t2, data={"close": ts[i], "open": 1.4})
self.assertEquals([{
'value': np.nan
}, {
'value': np.nan
}], stddev.get_data())
t3 = nextTime(t2)
i = i + 1
bar.add(timestamp=t3, data={"close": ts[i], "open": 1.8})
self.assertEquals([{
'value': np.nan
}, {
'value': np.nan
}, {
'value': np.std(ts)
}], stddev.get_data())
def test_nan_before_size(self):
bar = self.app_context.inst_data_mgr.get_series("bar")
bar.start(self.app_context)
stddev = StdDev(bar, input_key='close', length=3)
stddev.start(self.app_context)
t1 = datetime.datetime.now()
nextTime = lambda t : t + datetime.timedelta(0,3)
x = np.random.normal(0, 2.0, 3)
ts = np.cumsum(x) + 100
i = 0
bar.add({"timestamp": t1, "close": ts[i], "open": 0})
self.assertEquals([{"name": "'%s'" % stddev.name,
"timestamp": t1,
'value': np.nan}],
stddev.get_data())
t2 = nextTime(t1)
i = i+1
bar.add({"timestamp": t2, "close": ts[i], "open": 1.4})
self.assertEquals([{"name": "'%s'" % stddev.name, "timestamp": t1, 'value': np.nan},
{"name": "'%s'" % stddev.name, "timestamp": t2, 'value': np.nan}],
stddev.get_data())
t3 = nextTime(t2)
i = i+1
bar.add({"timestamp": t3, "close": ts[i], "open": 1.8})
self.assertEquals([{"name": "'%s'" % stddev.name, "timestamp": t1, 'value': np.nan},
{"name": "'%s'" % stddev.name, "timestamp": t2, 'value': np.nan},
{"name": "'%s'" % stddev.name, "timestamp": t3, 'value': np.std(ts)}],
stddev.get_data())
def test_empty_at_initialize(self):
close = self.app_context.inst_data_mgr.get_series("bar")
stddev = StdDev(close, input_key='close', length=3)
self.assertEquals(0, len(stddev.get_data()))
def test_name(self):
bar = self.app_context.inst_data_mgr.get_series("bar")
stddev = StdDev(bar, input_key='close', length=3)
self.assertEquals("StdDev('bar',close,3)", stddev.name)
def test_empty_at_initialize(self):
close = self.app_context.inst_data_mgr.get_series("bar")
stddev = StdDev(close, input_key='close', length=3)
self.assertEquals(0, len(stddev.get_data()))
